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Project Overview:
Walkability is becoming an important standard for livable cities. The street network construction and low-carbon travel initiatives promote macro-scale urban planning and community development. The pandemic has brought health crises to communities, people are attaching great importance to the pursuit of health and well-being. Currently walking navigation on the market focuses mostly on getting users from A to B, the project intends to make the walking experience more fun, and cater to personal needs.
Go Street is a mobile application for urban street walking indexes measurement and navigation. It involves transforming and applying big data from the streets and surroundings to people's daily lives.
Project Background
Walking is the most popular form of exercise among adults in the United States, more than 145 million adults include walking as part of a physically active lifestyle.
More and more people are Health and Fitness App users. Over 80 million in 2022 use Health and Fitness apps, 38% more than in 2019.
Walking as the most simple exercise has tremendous physical and mental benefits.
Walking dramatically lower each individual’s carbon footprint. One study concluded that walking a mile and a half would release 75% less greenhouse gases.
The Challenge
Use San Francisco as an example, many of us walk to our destinations, whether it's a restaurant, a coffee shop, or
Competitor Analysis
We looked at a few navigation apps on the market, almost all of them have the function of customizing routes based on distance, but very few customize the routes based on experiences, such as passing fewer traffic lights, walking on streets with more trees shade.
On a warm summer day, what if the app linked the weather data and plan a route that passes a convenience store or even an ice cream store because you like ice cream?
CHALLENGE
How can we transform the current indexes and data to meet user’s scenario-based and personalized needs?
NEEDFINDING
There were 30 respondents participated in the interview. The interview aims to understand our users’ current behaviors, needs, and motivations during walking activities. The core interview questions cover the user’s basic information, goals, walking contexts and conditions, emotions, as well as their current solutions if encountering problems.
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Among these interviewees, we found that using the goals of walking to distinguish user groups is the most intuitive way, because the user's behaviors and the way of evaluating the street environment will be clearly distinguished based on their motivation to go out. According to the motivation of walking activities, users are mainly divided into three types, they are: fun-oriented shopping activities, health-oriented running and walking activities, and scenic viewing-oriented traveling activities. We abstracted users' key feedback to reflect their corresponding needs and pain points.
Look for fun: for pedestrians going somewhere and wanting to find interesting places along the way
Look for health: for users running/exercise regularly and have the needs to customize their routes
Look for sightseeing: for users exploring somewhere new and need a 'walk plan'
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PERSONA
We created three personas beased on each one's goal, which represents our target users.
Suki Zhou: A woman lives in the city and is always interested in finding a few new places along the way while walking to destinations.
Jay Wong: A Middle-aged man that wants to keep a healthy lifestyle. Walking and running are his main exerciese.
Tiantian: She loves travel and plans tours.
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How can we develop synthetic strategies to fix the main pain points?
We further divide the stages of walking into more steps. We summarize the raw data from experience maps into concise phrases so we can clearly describe what happens at each stage of the interaction and see the common needs embodied by all the user groups.
Primary pain points
Users need to switch in between different apps to gather all the necessary information. (Yelp, weather, google maps, social media)
Current apps cannot recommend a route based on user’ s preferences on walking
Fear of uncertainty of exploring unfamiliar streets/ places
Opportunities
Integrate features of discovery and navigation and allow route customization based on user’s preference.
Allow other users to provide more up to date walking information
Personal walking history is provided for sharing with others
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Ideation